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Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)F-PET/CT

Background: 18-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-PET/CT) has been widely applied for the imaging of head and neck squamous cell carcinoma (HNSCC). This study examined whether pre- and post-treatment (18)F-PET/CT features can help predict the survival of HNSCC...

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Autores principales: Liu, Zheran, Cao, Yuan, Diao, Wei, Cheng, Yue, Jia, Zhiyun, Peng, Xingchen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7425452/
https://www.ncbi.nlm.nih.gov/pubmed/32674074
http://dx.doi.org/10.18632/aging.103508
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author Liu, Zheran
Cao, Yuan
Diao, Wei
Cheng, Yue
Jia, Zhiyun
Peng, Xingchen
author_facet Liu, Zheran
Cao, Yuan
Diao, Wei
Cheng, Yue
Jia, Zhiyun
Peng, Xingchen
author_sort Liu, Zheran
collection PubMed
description Background: 18-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-PET/CT) has been widely applied for the imaging of head and neck squamous cell carcinoma (HNSCC). This study examined whether pre- and post-treatment (18)F-PET/CT features can help predict the survival of HNSCC patients. Results: Three radiomics features were identified as prognostic factors. Radiomics score calculated from these features significantly predicted overall survival (OS) and disease-free disease (DFS). The clinicopathological characteristics combined with pre- or post-treatment nomograms showed better ROC curves and decision curves than the nomogram based only on clinicopathological characteristics. Conclusions: Combining clinicopathological characteristics with radiomics features of pre-treatment PET/CT or post-treatment PET/CT assessment of primary tumor sites as positive or negative may substantially improve prediction of OS and DFS of HNSCC patients. Methods: 171 patients who received pre-treatment (18)F-PET/CT scans and 154 patients who received post-treatment (18)F-PET/CT scans with HNSCC in the Cancer Imaging Achieve (TCIA) were included. Nomograms that combined clinicopathological features with either pre-treatment PET/CT radiomics features or post-treatment assessment of primary tumor sites were constructed using data from 154 HNSCC patients. Receiver operating characteristic (ROC) curves and decision curves were used to compare the predictions of these models with those of a model incorporating only clinicopathological features.
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spelling pubmed-74254522020-08-25 Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)F-PET/CT Liu, Zheran Cao, Yuan Diao, Wei Cheng, Yue Jia, Zhiyun Peng, Xingchen Aging (Albany NY) Research Paper Background: 18-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-PET/CT) has been widely applied for the imaging of head and neck squamous cell carcinoma (HNSCC). This study examined whether pre- and post-treatment (18)F-PET/CT features can help predict the survival of HNSCC patients. Results: Three radiomics features were identified as prognostic factors. Radiomics score calculated from these features significantly predicted overall survival (OS) and disease-free disease (DFS). The clinicopathological characteristics combined with pre- or post-treatment nomograms showed better ROC curves and decision curves than the nomogram based only on clinicopathological characteristics. Conclusions: Combining clinicopathological characteristics with radiomics features of pre-treatment PET/CT or post-treatment PET/CT assessment of primary tumor sites as positive or negative may substantially improve prediction of OS and DFS of HNSCC patients. Methods: 171 patients who received pre-treatment (18)F-PET/CT scans and 154 patients who received post-treatment (18)F-PET/CT scans with HNSCC in the Cancer Imaging Achieve (TCIA) were included. Nomograms that combined clinicopathological features with either pre-treatment PET/CT radiomics features or post-treatment assessment of primary tumor sites were constructed using data from 154 HNSCC patients. Receiver operating characteristic (ROC) curves and decision curves were used to compare the predictions of these models with those of a model incorporating only clinicopathological features. Impact Journals 2020-07-16 /pmc/articles/PMC7425452/ /pubmed/32674074 http://dx.doi.org/10.18632/aging.103508 Text en Copyright © 2020 Liu et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Liu, Zheran
Cao, Yuan
Diao, Wei
Cheng, Yue
Jia, Zhiyun
Peng, Xingchen
Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)F-PET/CT
title Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)F-PET/CT
title_full Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)F-PET/CT
title_fullStr Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)F-PET/CT
title_full_unstemmed Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)F-PET/CT
title_short Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)F-PET/CT
title_sort radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)f-pet/ct
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7425452/
https://www.ncbi.nlm.nih.gov/pubmed/32674074
http://dx.doi.org/10.18632/aging.103508
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